You have an existing skillset that extracts text and entities. You now need to add a custom skill that translates the extracted text to English. The custom skill is already deployed as an Azure Function. What is the minimal change to the skillset?

Rebuild the data source to include translated text

Modify the indexer to call the Function directly

Create a new index with a translation field

Add a skill definition that references the Function's URL and maps its input from the text output of the previous skill

A multinational company needs to search across documents in multiple languages. They want to find documents that are conceptually similar to a query, even if the query is in a different language than the document. They also need to keep the enrichment pipeline maintainable. What should you implement?

Create separate indexes for each language and query them all

Use the built-in language detection skill and translate all documents to English before indexing

Use a multilingual embedding model in a custom skill to generate vectors, and store them in a vector field in the index

Use semantic search with a multilingual configuration

A legal research platform uses Azure AI Search. Users search for case law using natural language queries. The current keyword search returns many irrelevant results. They want to improve relevance without changing the index schema. What should they do?

Create a new index with additional fields for semantic ranking.

Add more synonyms to the index to expand query matching.

Use a custom skill to re-rank results at query time.

Enable semantic search on the existing index and configure a semantic configuration using existing fields.

What is the purpose of an index in Azure AI Search?

To store the original source documents in a structured format

To apply AI enrichment to raw data during ingestion

To connect to external data sources and pull data automatically

To define the schema of fields and how data is stored and searched

Microsoft Certified:Azure AI Engineer Associate

Domain 6Objective 1

Implement an Azure AI Search Solution AI-102 Practice Questions (Page 1)

Part of the Implement knowledge mining and information extraction solutions domain, which accounts for 15-20% of the AI-102 exam. Microsoft does not publish an official question count, but from its 100-minute exam (~40–65 total, ~6–13 in this domain), expect 2–4 from this objective — we provide 55 practice questions to prepare you well beyond it. (estimate)

55questions here

11free pages

12concepts

15-20%of the exam

Questions 1–5

1foundation · easy
Where do you define a custom skill so that it is used during indexing?
Select an answer first
2application · medium
You have an existing skillset that extracts text and entities. You now need to add a custom skill that translates the extracted text to English. The custom skill is already deployed as an Azure Function. What is the minimal change to the skillset?
Select an answer first
3expert · hard
A multinational company needs to search across documents in multiple languages. They want to find documents that are conceptually similar to a query, even if the query is in a different language than the document. They also need to keep the enrichment pipeline maintainable. What should you implement?
Select an answer first
4expert · hard
A legal research platform uses Azure AI Search. Users search for case law using natural language queries. The current keyword search returns many irrelevant results. They want to improve relevance without changing the index schema. What should they do?
Select an answer first
5foundation · easy
What is the purpose of an index in Azure AI Search?
Select an answer first

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Implement an Azure AI Search Solution AI-102 Practice Questions (Page 1)

Questions 1–5

Where do you define a custom skill so that it is used during indexing?

You have an existing skillset that extracts text and entities. You now need to add a custom skill that translates the extracted text to English. The custom skill is already deployed as an Azure Function. What is the minimal change to the skillset?

A legal research platform uses Azure AI Search. Users search for case law using natural language queries. The current keyword search returns many irrelevant results. They want to improve relevance without changing the index schema. What should they do?

What is the purpose of an index in Azure AI Search?

Keep studying — Implement knowledge mining and information extraction solutions